Instructions to use emre/speecht5_tts_tr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emre/speecht5_tts_tr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="emre/speecht5_tts_tr")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("emre/speecht5_tts_tr") model = AutoModelForTextToSpectrogram.from_pretrained("emre/speecht5_tts_tr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d84fa6ce571bcca8327088068f34b98890db7c4cd0ebfb6a6272d982091cd7d4
- Size of remote file:
- 4.09 kB
- SHA256:
- 2ad581f2f85b517e7040d7616694364cb0bfe22735b1e0bd4515638a1b373ef4
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